磁敏测速系统的数据采集平台实现

串口同步采集是工业控制应用的重要环节,为克服由于不准确的数据采集所带来的乘性误差,进而对多串口的同步采集进行了研究。利用VS2005编程环境,设计实现了多串口的上位机数据采集平台,该平台开辟线程对多个串口采取重叠读取方式,实现了对测速系统中大量的串口数据同步读取、保存并实现波形动态显示的功能,满足了智能测速系统的测速算法研究的需要。此平台可以广泛的应用在测速系统之中,也可辅助用于各种工业控制的高级要求。     

基于ZigBee的多机器人通信系统的设计

为解决多机器人协作的问题,设计了可以让机器人之间基于ZigBee网络进行通信的通信方案。机器人硬件系统中引入了ZigBee节点,多个机器人依赖ZigBee形成一个星型网络,每个机器人可以通过中心节点保持通信。实验结果表明,机器人之间可以可靠地进行通信,能够显著提高机器人的工作效率。     

两轴独立的高精度齿形加工数字控制系统

论述了梳理齿条冲齿机的工作原理,控制策略及系统实现,给出了软件编程方法与通信实现.系统采用人机界面和数字通信,实现了冲齿-牵引机构的两轴同步驱动和加工参数的柔性调整.     

Differentially expressed proteins of MCF-7 human breast cancer cells affected by Zilongjin, a complementary Chinese herbal medicine

Purpose : Zilongjin, a complementary Chinese herbal medicine, has been used to alleviate the adverse effects of chemotherapeutic drugs in cancer therapy. However, the mechanisms of anti‐cancer activity of Zilongjin are still largely unkonwn. Experimental design : First, the proteomic approach of combined 2‐DE and ESI‐MS/MS was used to investigate the effect of Zilongjin on the protein expression in MCF‐7 cells. Then, the differential expression of some proteins was confirmed by Western blot, cytoimmunofluoresecnce, and quantitative real‐time RT‐PCR analysis. Results : The identified proteins with differential expression, involved in such events as protein translation, cellular signal transduction, cytoskeleton formation and transportation, include seven downregulating proteins, such as Eukaryotic translation initiation factor 3 subunit I, Eukaryotic translation initiation factor 1A Y‐chromosomal, Ran‐specific GTPase‐activating protein, Ubiquitin‐conjugating enzyme E2 N, Tropomodulin‐3, Macrophage‐capping protein, and Tumor protein D52, as well as two upregulating proteins, HSP β‐1 and keratin18. Moreover, the differential expression of three proteins was confirmed. Conclusions and clinical relevance : (i) These results provide a new insight into the molecular mechanisms of Zilongjin on therapy for breast cancer. (ii) The application of the proteomic approaches will result in the more extended appreciation of Chinese medicine than those known at present.     

Health Outcomes and Socio-economic Status Among the Elderly in China: Evidence from the CHARLS Pilot

We are concerned in this paper with measuring health outcomes among the elderly in Zhejiang and Gansu provinces, China, and examining the relationships between different dimensions of health status and measures of socio-economic status (SES). We are CHARLS pilot data to document health conditions, using a very rich set of health indicators that include both self-reported measures and biomarkers. We also examine correlations between these health outcomes and two important indicators of socio-economic status (SES): education and log of per capita expenditure (log pce), our preferred measure of household resources. In general education tends to be positively correlated with better health outcomes, as it is in other countries. However, unmeasured community influences turn out to be highly important, much more so than one usually finds in other countries. While it is not yet clear which aspects of communities matter and why they matter, we set up an agenda for future research on this topic. We also find a large degree of under-diagnosis of hypertension, a major health problems that afflicts the aged. This implies that the current health system is not well prepared to address the rapid aging of the Chinese population, at least not in Gansu and Zhejiang.     

STRINGVACUA. A Mathematica package for studying vacuum configurations in string phenomenology

We give a simple tutorial introduction to the Mathematica package STRINGVACUA, which is designed to find vacua of string-derived or inspired four-dimensional N=1 supergravities. The package uses powerful algebro-geometric methods, as implemented in the free computer algebra system Singular, but requires no knowledge of the mathematics upon which it is based. A series of easy-to-use Mathematica modules are provided which can be used both in string theory and in more general applications requiring fast polynomial computations. The use of these modules is illustrated throughout with simple examples.

Program summary

Program title: STRINGVACUACatalogue identifier: AEBZ_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBZ_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: GNU GPLNo. of lines in distributed program, including test data, etc.: 31 050No. of bytes in distributed program, including test data, etc.: 163 832Distribution format: tar.gzProgramming language: “Mathematica” syntaxComputer: Home and office spec desktop and laptop machines, networked or stand aloneOperating system: Windows XP (with Cygwin), Linux, Mac OS, running Mathematica V5 or aboveRAM: Varies greatly depending on calculation to be performedClassification: 11.1External routines: Linux: The program “Singular” is called from Mathematica. Windows: “Singular” is called within the Cygwin environment from Mathematica.Nature of problem: A central problem of string-phenomenology is to find stable vacua in the four-dimensional effective theories which result from compactification.Solution method: We present an algorithmic method, which uses techniques of algebraic geometry, to find all of the vacua of any given string-phenomenological system in a huge class.Running time: Varies greatly depending on calculation requested.     

A note on on-line broadcast scheduling with deadlines

In this paper, we study an on-line broadcast scheduling problem with deadlines, in which the requests asking for the same page can be satisfied simultaneously by broadcasting this page, and every request is associated with a release time, deadline and a required page with a unit size. The objective is to maximize the number of requests satisfied by the schedule. In this paper, we focus on an important special case where all the requests have their spans (the difference between release time and deadline) less than 2. We give an optimal online algorithm, i.e., its competitive ratio matches the lower bound of the problem.     

A self-organising mixture autoregressive network for FX time series modelling and prediction

Nowadays a great deal of effort has been made in order to gain advantages in foreign exchange (FX) rates predictions. However, most existing techniques seldom excel the simple random walk model in practical applications. This paper describes a self-organising network formed on the basis of a mixture of adaptive autoregressive models. The proposed network, termed self-organising mixture autoregressive (SOMAR) model, can be used to describe and model nonstationary, nonlinear time series by means of a number of underlying local regressive models. An autocorrelation coefficient-based measure is proposed as the similarity measure for assigning input samples to the underlying local models. Experiments on both benchmark time series and several FX rates have been conducted. The results show that the proposed method consistently outperforms other local time series modelling techniques on a range of performance measures including the mean-square-error, correct trend predication percentage, accumulated profit and model variance.     

Structure identification of Bayesian classifiers based on GMDH

This paper introduces group method of data handing (GMDH) theory to Bayesian classification, and proposes GMBC algorithm for structure identification of Bayesian classifiers. The algorithm combines two structure identification ideas of search & scoring and dependence analysis, and is able to accomplish the process of adaptive structure identification. We experimentally test two versions of Bayesian classifiers (GMBC-BDe and GMBC-BIC) over 25 data sets. The results show that, the structure identification of the two Bayesian classifiers especially GMBC-BDe is very effective. And when the data sets contain lots of noise, the superiority of Bayesian classifiers learned by GMBC is more obvious. Finally, giving a classification domain without any prior information about the noise, we recommend adopting GMBC-BDe rather than GMBC-BIC.